if analyze_organelle == 'nucleoli':
nuclear_pd.to_csv('%s/data_nuclear.txt' % storage_path,
index=False,
sep='\t')
# images
dis.plot_offset_map(pointer_pd, fitting_mode, 'bg',
storage_path) # offset map
dis.plot_raw_intensity(pointer_pd, ctrl_pd_ft, fitting_mode, 'bg',
storage_path) # raw intensity
dis.plot_pb_factor(pointer_pd, 'bg',
storage_path) # photobleaching factor
dis.plot_corrected_intensity(
pointer_pd, fitting_mode, 'bg',
storage_path) # intensity after dual correction
dis.plot_normalized_frap(pointer_pd, fitting_mode, 'bg',
storage_path) # normalized FRAP curves
# normalized FRAP curves after filtering with fitting
# individual normalized FRAP curves with fitting
dis.plot_frap_fitting(pointer_pd, fitting_mode, 'bg', storage_path)
else:
# --------------------------
# OUTPUT
# --------------------------
print("### Export data ...")
storage_path = save_path
if not os.path.exists(storage_path):
os.makedirs(storage_path)
# data_log
data_log.to_csv('%s/data_log.txt' % storage_path,
'optimal_mobile_fraction':
pointer_ft_pd['optimal_mobile_fraction'],
'optimal_t_half':
pointer_ft_pd['optimal_t_half'],
'optimal_slope':
pointer_ft_pd['optimal_slope']
})
pointer_out.to_csv('%s/data.txt' % storage_path, index=False, sep='\t')
# images
dis.plot_offset_map(pointer_pd, storage_path) # offset map
dis.plot_raw_intensity(pointer_pd, ctrl_pd_ft, storage_path) # raw intensity
dis.plot_pb_factor(pointer_pd, storage_path) # photobleaching factor
dis.plot_corrected_intensity(pointer_pd,
storage_path) # intensity after dual correction
dis.plot_normalized_frap(pointer_pd, storage_path) # normalized FRAP curves
dis.plot_frap_fitting(
pointer_pd,
storage_path) # normalized FRAP curves after filtering with fitting
# individual normalized FRAP curves with fitting
# --------------------------
# OUTPUT DISPLAY
# --------------------------
if display_mode == 'Y':
print("### Output display ...")
with napari.gui_qt():
# embed mpl widget in napari viewer
mpl_widget = FigureCanvas(Figure(figsize=(5, 3)))
[ax1, ax2, ax3] = mpl_widget.figure.subplots(nrows=1, ncols=3)